System and methods for non-parametric technique based geolocation and cognitive sensor activation

A method for providing geolocation information in a multi-path environment comprising the steps of:

• receiving a mixture of signals from one or more emitters at one or more sensors in said multi-path environment;
• determining angle of arrival (AOA) and time of arrival (TOA) data from each of the received signals in said multi-path environment;
• clustering the mixture of received signals based on the determined AOA and TOA data into one or more clusters arising from one or more emitters utilizing a non-parametric Bayesian technique;
• transmitting by the one or more sensors the one or more clusters to a central node for further processing;
• estimating by the central node the time difference of arrival (TDOA) profile for each of the one or more emitters based on the one or more clusters and extracting the AOA data for said emitters from within the distinct one or more clusters;
• processing by the central node the AOA data and TDOA profile data for each of the one or more emitters to perform a hybrid AOA-TDOA technique for determining the geolocation of the one or more emitters;
• wherein the central node further utilizes a Dirichlet process mixture model (DPMM) technique to determine an actual number of emitters comprising the one or more emitters;
• and
• selectively activating the one or more sensors to detect the corresponding one or more emitters based on the determined geolocation of the one or more emitters.

A method for selectively activating one or more sensors for tracking one or more emitters in a multi-path environment, comprising the steps of:

• receiving signals from one or more emitters at one or more sensors in said multi-path environment;
• determining angle of arrival (AOA) and time of arrival (TOA) from each of the received signals in said multi-path environment;
• clustering into clusters the mixture of received signals arising from one or more emitters utilizing a non-parametric Bayesian technique;
• transmitting by the one or more sensors said clusters to a central node for further processing;
• estimating by the central node the time difference of arrival (TDOA) profile for each of the one or more emitters and extracting the AOA data for said emitters from within the distinct clusters;
• processing by the central node the TDOA profile and AOA data information for each of the one or more emitters to perform a hybrid AOA-TDOA technique for determining the geolocation of the one or more emitters, wherein the central node further utilizes a Dirichlet process mixture model (DPMM) technique to determine an actual number of emitters comprising the one or more emitters;
• tracking the position and a next time instant position of each of the emitters based on said geolocation of the one or more emitters;
• and
• selectively activating the one or more sensors in proximity to one or more emitters based on the determined geolocation and next time instant position of the one or more emitters.